Before launch, product leaders must ask if their AI offering is a true product or just a feature. Slapping an AI label on a tool that automates a minor part of a larger workflow is a gimmick. It will fail unless it solves a core, high-friction problem for the customer in its entirety.

Marketers win with AI not by making existing tasks faster, but by using it to unlock new growth opportunities. The focus should be on game-changing programs that drive revenue, rather than on simply achieving incremental efficiency gains.

Large publishers find that while users love new AI conversational features, the underlying inference costs are prohibitively expensive. They can only test on a tiny fraction of their traffic. This financial pain point is the primary driver for adopting new monetization platforms.

Data from RAMP indicates enterprise AI adoption has stalled at 45%, with 55% of businesses not paying for AI. This suggests that simply making models smarter isn't driving growth. The next adoption wave requires AI to become more practically useful and demonstrate clear business value, rather than just offering incremental intelligence gains.

AI makes it cheaper to build new features. Instead of passing these savings on through lower prices, companies should use this efficiency to expand their product's scope to solve adjacent customer problems. This bundling strategy increases the overall value proposition, allowing you to charge more and become more integral.

The market is rejecting 'lame co-pilots' that provide minor workflow improvements for an extra fee. Successful AI products create entirely new, powerful use cases and deliver substantial, tangible value on day one, justifying their place in the budget.

Adding a chat interface or minor "AI features" won't unlock new budget. To capture significant AI spend, your product must either replace human headcount, make users dramatically more effective, or provide an order-of-magnitude productivity increase.

Founders can get lost building complex AI systems and automations. This can become a trap, a "procrastination machine," that feels productive but doesn't contribute to the primary goal of generating revenue. Always ask if the AI work is actually making the business money.

The bar for new AI products is exceptionally high. Customers expect transformative results, like replacing multiple hires or generating six-figure revenue on day one. Products offering only incremental productivity gains will be ignored by a market flooded with high-ROI options.